Dynamic Virtual Simulation with Real-Time Haptic Feedback for Robotic Internal Mammary Artery Harvesting

被引:0
作者
Wang, Shuo [1 ]
Ren, Tong [2 ,3 ]
Cheng, Nan [2 ]
Wang, Rong [2 ]
Zhang, Li [1 ]
机构
[1] Tsinghua Univ, Dept Engn Phys, Key Lab Particle & Radiat Imaging, Minist Educ, Beijing 100084, Peoples R China
[2] Peoples Liberat Army Gen Hosp, Dept Adult Cardiac Surg, Sr Dept Cardiol, Med Ctr 6, Fucheng Rd, Beijing 100048, Peoples R China
[3] Chinese PLA Med Sch, Fuxing Rd, Beijing 100089, Peoples R China
来源
BIOENGINEERING-BASEL | 2025年 / 12卷 / 03期
基金
中国国家自然科学基金;
关键词
robotic cardiac surgery; coronary artery bypass grafting; internal mammary artery; surgical training; haptic feedback;
D O I
10.3390/bioengineering12030285
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
Coronary heart disease, a leading global cause of mortality, has witnessed significant advancement through robotic coronary artery bypass grafting (CABG), with the internal mammary artery (IMA) emerging as the preferred "golden conduit" for its exceptional long-term patency. Despite these advances, robotic-assisted IMA harvesting remains challenging due to the absence of force feedback, complex surgical maneuvers, and proximity to the beating heart. This study introduces a novel virtual simulation platform for robotic IMA harvesting that integrates dynamic anatomical modeling and real-time haptic feedback. By incorporating a dynamic cardiac model into the surgical scene, our system precisely simulates the impact of cardiac pulsation on thoracic cavity operations. The platform features high-fidelity representations of thoracic anatomy and soft tissue deformation, underpinned by a comprehensive biomechanical framework encompassing fascia, adipose tissue, and vascular structures. Our key innovations include a topology-preserving cutting algorithm, a bidirectional tissue coupling mechanism, and dual-channel haptic feedback for electrocautery simulation. Quantitative assessment using our newly proposed Spatial Asymmetry Index (SAI) demonstrated significant behavioral adaptations to cardiac motion, with dynamic scenarios yielding superior SAI values compared to static conditions. These results validate the platform's potential as an anatomically accurate, interactive, and computationally efficient solution for enhancing surgical skill acquisition in complex cardiac procedures.
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页数:20
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